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There are many conjectures that we know are almost surely true, but we don't know why, and explaining why is the main purpose of the mathematician when publishing a proof.

The fact that we don't know why is a clue pointing at some area of math that we haven't discovered yet. The hope is always that it will uncover some hidden fertile valley that will lead to lots of new discoveries. But the proof of the conjecture itself, without understanding, is really not that valuable.

My point is that even if AI discovers many new truths, there's still plenty to do for the mathematical community, in dissecting it and building useful abstractions to understand it, abstractions that can be leveraged for further exploration and uncovering new questions.

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This seems right as long as the AI output is legible enough to reverse-engineer
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> 1. People will publish so much frontier mathematics, humans won't be able to understand it all

That already happened before AI.

> 2. Frontier mathematics will all be kept secret

Gauss kept lots of frontier mathematics in his drawer. In the 20th centuries government spy agencies developed public key cryptography long before that was known to the public. To give just two examples.

It's not the end of the world.

And what do you care, if someone keeps frontier mathematics a secret, if you can ask DeepSeek version 10 in 2030 to prove the Riemann hypothesis for you?

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> long before that was known to the public

About 4-6 years earlier, depending what you want to count, although the inventors may also have been less clear on its importance or applications compared to the later public inventors.

https://en.wikipedia.org/wiki/Public-key_cryptography#Classi...

I guess that's kind of a long time in computer technology terms.

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Was the term "frontier mathematics" always in use, or did it just become a thing after the advent of contemporary AI?
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It's been in use far longer than LLMs. Thought I'm not exactly sure when it came into common use. I'm pretty sure I've heard the term on Nova decades ago.
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I think the worry is:

1. People will publish AI generated frontier math making it difficult to identify frontier mathematicians. 2. Trained frontier mathematicians will become scarce

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Seems perfectly possible to get the worst of both worlds: more mathematics than anyone can read, and less access to the mathematics people actually care about.
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You don't think frontier mathematics is already secret?
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How to admit you're in finance without admitting you're in finance?
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Or Cryptanalysis.

" The National Security Agency is the largest employer of mathematicians in the U.S. "

https://www.scientificamerican.com/article/mathematicians-an...

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Or signals intelligence.
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unfortunately, the worse of both can be true at once.
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That's also what the gerrymandering discourse is like. Gerrymandering is a threat to civilization because it means political parties will minimize their electoral margins, and because it means politicians will maximize their electoral margins.
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Like yeah, result is that one group politicians are minimized and others maximized.

Which makes total sense unlike the "too much frontier math" nonsense.

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> Like yeah, result is that one group politicians are minimized and others maximized.

Which groups are those?

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The whole point of gerrymandering is to split districts so that votes for the other party are diluted. The whole point is to create many districts where your party is majority and then a few districts for the rest of the opposition.

If you are good at it, end result is that minority can keep majority of the seats and power. So, as there are two parties, the groups are "likely to voted republicans" and "likely to vote democrats".

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